{"uid":"cap_tPVjwknLgUblA6PTkxHOS","slug":"orbonomy-llm-batch-processing-bac4d744","name":"Orbonomy LLM Batch Processing","description":"50+ pay-per-call API endpoints across accommodation, AI, content, fact-checking, and data services. Powered by x402 protocol.","url":"https://backup-v2api.orbonomy.xyz/api/llm/batch","method":"POST","headers":{},"bodySchema":{"type":"object","required":["items","system_prompt"],"properties":{"items":{"type":"array"},"system_prompt":{"type":"string"}}},"responseSchema":{"type":"object","properties":{"success":{"type":"boolean"}}},"example":null,"exampleRequest":null,"tags":["x402"],"displayCostAmount":"0.1","displayCostAsset":"USDC","priceDynamic":false,"priceHint":null,"priceStatus":"priced","priceSource":"probe","requiresHandshake":false,"reviewCount":0,"rating":{"score":"0.00","successRate":"0.00","reviews":0,"stars":null,"state":"unrated"},"availabilityStatus":"unknown","priceObserved":null,"sessionDeposit":null,"pricing":{"kind":"static","summary":"$0.1/call","primary":{"kind":"static","protocol":"x402","network":"base","amountUsd":"0.1","per":"call","confidence":"exact"},"accepted":[{"kind":"static","protocol":"x402","network":"base","amountUsd":"0.1","per":"call","confidence":"exact"}]},"paymentMethods":[{"uid":"pm_fMy__jL_s9nePGz1Nd3kW","protocol":"x402","methodType":"crypto","chain":"base","mode":"charge","costAmount":"0.1","costPer":"request","priority":0,"asset":null,"unit":"request","depositMicros":null,"planRef":null}],"brandName":null,"brandSlug":null,"brandBaseUrl":null,"brandDocsUrl":null,"whatItDoes":"Runs a batch of items through a language model using a shared system prompt, returning structured results for each item","exampleAgentPrompt":"Use Orbonomy's batch LLM endpoint to classify each of these 5 customer reviews as positive, negative, or neutral — use the system prompt: 'You are a sentiment classifier. Reply with one word: positive, negative, or neutral.' and send all 5 reviews as the items array.","exampleUseCases":[{"title":"Extract key entities from support tickets","prompt":"I have 20 support tickets sitting in my queue and need to pull out the customer issue type and urgency level from each one. Can you batch these through Orbonomy with a system prompt that extracts just those two fields as structured JSON for every ticket?"},{"title":"Moderate product reviews at scale","prompt":"We just got 150 new user reviews for our app and I need to flag any that contain profanity, harassment, or spam before they go live. Run them all through Orbonomy with a moderation prompt that marks each review as safe or needs_review."},{"title":"Summarize research papers quickly","prompt":"I have a folder of 12 academic papers on climate science and need one-sentence summaries of the findings from each. Can you send them all to Orbonomy at once using a system prompt that extracts just the key conclusion from every paper?"}],"resultDescription":"A JSON object with a 'success' boolean field and, on success, processed results for each item in the batch as transformed/generated by the LLM according to the system prompt","failureModes":["Empty items array returns error or empty results","Missing system_prompt field causes a 400 validation error","Oversized batch may hit payload or token limits","Payment failure via x402 protocol returns 402 Payment Required","LLM inference timeout for very large batches","Invalid item types in the array may cause processing errors"],"whenToPreferThis":"Choose this endpoint when you need to apply the same LLM instruction to multiple items in a single API call, avoiding the overhead of multiple individual requests. Ideal for bulk classification, extraction, summarization, or transformation tasks where a consistent system prompt should govern all outputs. Best suited for workflows where cost efficiency and batching are priorities over real-time single-item processing.","instructions":null,"reviewSummary":null,"reviewSummaryHighlights":null,"reviewSummaryConcerns":null,"reviewSummaryGeneratedAt":null,"activationCount":0,"lastUsedAt":null,"lastSuccessfullyRanAt":null,"lastHealthCheckAt":"2026-09-15T12:46:12.814Z","isFirstParty":false}